Exploring molecular fragments for fraction unbound in human plasma of chemicals: a fragment-based cheminformatics approach

被引:1
|
作者
Banerjee, S. [1 ]
Bhattacharya, A. [2 ]
Dasgupta, I. [2 ]
Gayen, S. [2 ]
Amin, S. A. [1 ]
机构
[1] JIS Univ, Dept Pharmaceut Technol, Kolkata, India
[2] Jadavpur Univ, Dept Pharmaceut Technol, Lab Drug Design & Discovery, Kolkata, India
关键词
Fraction unbound in plasma; QSAR; machine learning; fingerprint; fragments; ECFP; IN-SILICO PREDICTION; PROTEIN-BINDING; DRUG DISCOVERY; SPACE NETWORKS; QSAR MODELS; CLASSIFICATION; INHIBITORS; MUTAGENICITY; DESIGN;
D O I
10.1080/1062936X.2024.2415602
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Fraction unbound in plasma (fu,p) of drugs is an significant factor for drug delivery and other biological incidences related to the pharmacokinetic behaviours of drugs. Exploration of different molecular fragments for fu,p of different small molecules/agents can facilitate in identification of suitable candidates in the preliminary stage of drug discovery. Different researchers have implemented strategies to build several prediction models for fu,p of different drugs. However, these studies did not focus on the identification of responsible molecular fragments to determine the fraction unbound in plasma. In the current work, we tried to focus on the development of robust classification-based QSAR models and evaluated these models with multiple statistical metrics to identify essential molecular fragments/structural attributes for fractions unbound in plasma. The study unequivocally suggests various N-containing aromatic rings and aliphatic groups have positive influences and sulphur-containing thiadiazole rings have negative influences for the fu,p values. The molecular fragments may help for the assessment of the fu,p values of different small molecules/drugs in a speedy way in comparison to experiment-based in vivo and in vitro studies.
引用
收藏
页码:817 / 836
页数:20
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